Toxic heavy metals are some of the most common hazardous pollutants found in industrial wastewater. Many metal ions, if present at higher than normal concentration, can pose a serious threat to the environment, animals, and humans. Current technologies for metal removal, such as chemical precipitation, electrochemical treatment and ion exchange, provide only a partially effective treatment, yet at high capital and operational costs, especially when the metal concentration is low. A promising, inexpensive and green alternative is to employ microbial biomass to remove and recover toxic metal ions from industrial wastewater. Among the main biomass types, abundant biomass produced as a waste byproduct of large-scale industrial processes (e.g., fermentation) can be a very inexpensive source of metal sorbent. The research firstly screened a series of industrial biomass wastes for effective metal removal. Then it was focused on characterizing experimentally the removal of heavy metals by freeze-dried brewery yeast waste (Saccharomyces cerevisiae), filamentous fungal waste and vitasoy waste. This research also aimed to develop a simple and effective mechanistic equilibrium model capable of predicting the performance of the metal biosorption process. The applicability of three types of surface complexation models (SCM), namely, constant capacitance model (CCM), diffuse layer model (DLM) and stern model (SM), with different binding site combinations to simulate the metal biosorption data was tested. Freeze-dried brewery yeast waste, collected from a beer corporation, was found to exhibit good Cu(II) and Cr(III) removal capacities. The effects of pH, ionic strength, and anions on the removal of Cu(II) and Cr(III) were studied. Biosorption of the Cu(II) and Cr(III) was strongly affected by solution pH. Isotherms for the biosorption of Cu(II) and Cr(III) on yeast biomass were developed. While the equilibrium data of Cu(II) fitted well to the linearized Freundlich model, the Cr(III) data fitted well to the linearized and non-linearized forms of Langmuir and Freundlich models. The technique of scanning electron microscopy coupled with energy dispersive X-ray analysis (EDAX) showed that the heavy metal ions had exchanged with K⁺ on the cell wall of the yeast biomass. The analysis of the biomass by FT-IR spectroscopy indicated that RCOOH and RPO₄H were the major metal binding sites on the yeast biomass surface. The surface acid-base properties of the yeast biomass were studied by potentiometric titration. Constant capacitance model (CCM) was applied to interpret the results. A two-site model could be used to calculate the surface deprotonation constants. The CCM was further employed to simulate the biosorption of Cu(II) and Cr(III) by yeast. The two-site model was the best for simulating Cu(II) whereas the one-site model best for Cr(III). Filamentous fungal waste, collected from a Chinese Mainland biopharmaceutical company, was found to exhibit good Cu(II) and Cr(III) biosorption capacities. The effects of pH, ionic strength, and anions on the removal of Cu(II) and Cr(III) were studied. Isotherms for the biosorption of Cu(II) and Cr(III) on fungal biomass were developed. The equilibrium data of Cu(II) could be well fitted by both linearized Freundlich and non-linearized Langmuir models while linearized Freundlich model could well describe the Cr(III) data. The EDAX technique demonstrated that the K⁺ peak disappeared completely after the metal removal process. Analysis of the IR spectra before and after biosorption suggested that the RCOOH group was responsible for the metal biosorption. The surface acid-base properties of the fungal biomass were studied by potentiometric titration. A three-site CCM was found to best simulate the titration data, suggesting that the functional groups, RCOOH, RPO₄H and ROH, were available on its surface to bind metal ions. The CCM was further employed to simulate the biosorption of Cu(II) and Cr(III) by fungal biomass. The one-site model was the best for simulating the biosorption of both Cu(II) and Cr(III).EDTA pretreatment was found to enhance the Cr(VI) biosorption performance of the fungal waste by 30%. The effects of pH, ionic strength, and biomass concentration on Cr(VI) removal were studied. Biosorption of the Cr(VI) was strongly affected by pH. The pre-treated fungal biomass exhibited the highest Cr(VI) biosorption capacity at around pH 1 to 2. The Cr(VI) biosorption capacity decreased in the presence of sodium nitrate electrolyte. The equilibrium Cr(VI) biosorption data were well fitted by both linearized and non-linearized forms of Langmuir and Freundlich models. The FT-IR spectroscopic study of Cr(VI)-laden biomass clearly indicated that a new peak representing the Cr-O of Cr(VI) anion appeared after Cr(VI) biosorption. There was no observable interaction between Cr(III) and the biomass as deduced from the IR analysis. The result suggested that only the hexavalent species were involved in the biosorption process. Vitasoy waste, collected from a local soya-bean-milk manufacturing plant, exhibited good Cr(III) biosorption capacity. The effects of pH, ionic strength, and anions on Cr(III) removal were studied. The equilibrium Cr(III) biosorption data were best fitted by the linearized Freundlich isotherm model. The EDAX technique demonstrated that both the K⁺ and Ca²⁺ peaks disappeared completely after the metal removal process. Analysis of the IR spectra before and after biosorption suggested that the COOH, P=O and NHCOCH₃ groups may involve in the biosorption process. Potentiometric titration was used to study the surface acid-base properties of the vitasoy waste, indicating that the RCOOH and RPO₄H functional groups were available on its surface to bind metal ions. The Cr(III) biosorption data could be well simulated using RCOOH as the major binding site in the CCM. The one-site model was the best for simulating biosorption of Cr(III). Two bacterial isolates from a local activated sludge process, Pseudomonas pseudoalcaligenes and Micrococcus sp. showed good biosorption capacities towards Pb(II), Cu(II) and Ni(II) in solution. The metal sorption percentage of both single and binary metal systems was found to be dependent on biomass concentration, competing metal mole ratio and ionic strength. Three types of SCMs with different binding site combinations were applied to model mathematically the biosorption data of both systems. It was found that CCM coupled with two-site-two-pKₐ binding was capable of simulating very well most of the experimental biosorption data of these two bacterial species. The unfitness of the one-site-one-pKₐ model could be remarkably improved via addition of a hydrolyzed complex for P. pseudoalcaligenes but not for Micrococcus sp. The applicability of the two-site-two-pKₐ CCM to mathematically predict the influences of some common anions on the Cu(II) biosorption edge of Micrococcus sp. was tested. The results demonstrated that the simulation could predict very well the experimental data.

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